QUaternary fault strain INdicators database - QUIN 1.0 - first release from the Apennines of central Italy

We present QUIN, a “QUaternary fault strain INdicators database”, designed to integrate and unify published and unpublished local-scale geological information and derive strain parameters for structural and seismotectonic analyses. It provides data on 3339 Fault Striation Pairs (FSP; fault plane and slickenline), distributed within 455 survey sites. These are exposed along the intra-Apennine Quaternary extensional faults of Central Italy. The area covers an extent of ~550 km in a NW-SE direction. We give information on FSP location, attitude and kinematics, and deformation axes. We also provide an original shapefile of the faults hosting the FSP. A large amount of homogeneously distributed Quaternary fault/slip data help to clarify and implement the contemporary geometric and kinematic deformation pattern of Central Italy that appears scattered and incomplete whenever exclusively derived from earthquake data. The high-density of structural data can help investigate stress pattern heterogeneities at local scales, with relevance for new generations of hazard assessment evaluation and a better understanding of rupture propagation and related barriers.

well-constrained late Quaternary geological data for seismic hazard assessment in Central Italy. A local database of the coseismic surface effects following the 2016 Norcia earthquake (M w 6.5) is made available by Villani et al. 8 , which provides ~7000 records surveyed along the Mt. Vettore fault, of which 450 give complete information on dip/dip-direction, plunge/azimuth, and the rake for 97 data collected over an along-strike extent of a few tens of kilometres.
The main contribution of this paper (i.e., the first release of the QUIN database) is that it contains 3339 Fault-Striation Pair (FSP) records, consisting of both newly acquired data (1315) and data from the literature (2024) distributed within 455 structural sites (SS) located along the major Quaternary intra-Apennine faults of central Italy (Fig. 1a). The unpublished data are recovered from our field notebooks and maps collated over the last few decades, augmented with new fieldwork to fill information gaps. We focus on ~550 km along-strike of the Quaternary extensional belt of central Italy, for a total area of about 30,000 km 2 . The belt consists of interconnected normal and normal-oblique faults, responsible for earthquakes with M w up to 7.0 14 in a densely inhabited territory.
For each FSP, we provide information on the fault hosting the SS (hereinafter referred to as "Host Faults"), the geometric-kinematic parameters, and the quality parameters. Furthermore, we calculate the attitudes of the corresponding principal deformation axes, considering two scenarios and assuming the contractional axis at 45° and 30° in the slip plane (Fig. 1b). This choice is based on the observation that, at upper-crust levels, Andersonian rules assume that the rupture plane is orientated at 30° with the principal stress (σ1) 15 . At the same time, classic P-T deformation axes, measured at 45° and derived from focal mechanisms, may be compared for a preliminary representation of the SH min horizontal trajectories 16 .
FSP from our QUIN database contains areas that have undergone recent earthquake activity, but also contains areas that have been aseismic in instrumental times, which may need special attention for forthcoming seismic hazard analysis. The QUIN database contains comprehensive and homogenous information on Quaternary fault/slip and the related deformation field to be implemented with earthquake data to perform formal stress inversions at regional scales and investigates local-scale effects controlling active deformation, seismogenic faulting, and seismic hazard, in a region of high-seismogenic potential. In addition, it may be useful for further elaborations on structural analysis, geodynamic interpretation, geothermal and petroleum exploration.

Methods
Host faults. Well-exposed normal and normal/oblique fault systems with activity since Early Quaternary times (last 2.58 My 17 ) and, in some cases, Late Pliocene, are distributed across the mountain belt of peninsular Italy 18 . They crop out in different lithotypes, including platform-to-basinal Meso-Cenozoic limestones, Cenozoic siliciclastic turbidites, and Plio-Quaternary clastic infill of continental basins.
An original database of the fault traces hosting the SS is stored in ZENODO 19 . The Host Fault database functions to precisely locate each SS on a specific fault segment. Fault traces available in a pre-existing database (Fault2SHA 12 ), which covers the central-eastern sector of our study area, were not used for two main reasons: 1) need of homogeneity with the rest of the area not covered by Fault2SHA; 2) a better geographic fit between the SS and our fault traces, that were partially surveyed in the years during the structural data mapping, although spatial misfits between the two datasets are generally very small (<a few kilometres).
The Host Fault attribute table provides information on fault location, name and dip-direction, and the age of activity of the fault system containing the Host Faults. The fault traces were derived from the literature and locally from unpublished maps related to the newly acquired FSPs. We started from the online version of the Structural and Neotectonic Models of Italy (scale 1:500,000, CNR 20,21 ) and updated it with more detailed traces of Late Pleistocene-Holocene faults available within online maps and repositories 12,[22][23][24][25] . We also used some raster maps available online, among which the sheets of the Geological Map of Italy at scale 1:100,000 and 1:50,000, and the seismotectonic map of the Emilia-Romagna Region at scale 1:250,000 23 . Detailed information used to draw the fault traces was derived from all the papers used to compile the QUIN fault/slip database (see following sections).
The age of onset of the fault system extends across the time interval from Late Pliocene to Middle Pleistocene and, at a regional scale, is progressively younger towards the east [4][5][6][26][27][28][29] . All the Host Faults may be considered potentially seismogenic and of interest for seismic hazard assessment evaluation, either because of direct geological and/or seismological evidence of activity in Late Pleistocene-Holocene times or because they belong to Late Pliocene-Quaternary fault systems nucleated and developed during the present seismotectonic regime. Details on the age of the oldest and the youngest evidence of the fault activity may be found within the attribute table of the Host Fault shapefile provided with this paper 19 . Overall, all the Host Faults can be considered undifferentiated Quaternary in age.
In map view, the Host Faults delineate a NW-SE to NNW-SSE striking broad Quaternary tectonic province consisting of west-and east-dipping normal and normal-oblique faults (Fig. 1a). The west-dipping normal faults, which in places have controlled the growth of Late Pliocene-to-Quaternary basins, show evidence of Late Pleistocene to present activity 12,32 . Although characterized by a less evident morphological expression, the east-dipping normal faults show also show geological and seismological evidence of recent activity 6,[33][34][35][36] . Indeed, earthquake data (i.e., hypocenters and focal mechanisms) and seismic lines have led many authors to suggest that the west-and the east-dipping outcropping Quaternary faults detach at depth onto a common east-deepening basal detachment. This geometry is largely accepted in northern Italy [37][38][39][40][41][42] , but only recently suggested in central-southern Italy 36,43-45 . www.nature.com/scientificdata www.nature.com/scientificdata/ Steps for building the QUIN database. To build a unified and comprehensive database, we followed the following sequential steps: 1) We recovered published FSP data (only data with both fault plane and slickenline attitudes) surveyed along the major intra-Apennine faults of Central Italy. Where the fault-slip attitudes were not tabulated in the original data source, we graphically derived them from their stereographic representation within the original paper, using the Stereonet software 46,47 . We applied corrections to the projection of slickenlines attitudes on the fault plane (see next section). 2) We extracted unpublished data from our field booklets and accompanying maps for FSP data surveyed in the last few decades. We projected the corresponding SS in map view on a GIS platform and identified information gaps. 3) We performed new field campaigns (from 2018 to 2021) to fill gaps in data and locally integrate the information. 4) With the previous steps, we recovered a total of 3339 FSP (2024 from literature and 1315 original), measured at 455 survey sites (SS). Each FSP corresponds to the raw data record of the QUIN fault/slip database. 5) We identified with a quality code the precision in reading the FSP attitudes from the original stereoplots (see the Data Records section). 6) We identified the spatial coordinates of each SS by georeferencing the location maps from the literature or our booklets. In some cases, Latitude and Longitude coordinates were available. The precision of the geographic location was also identified with a quality code (see the Data Records section). 7) Starting from the FSP data, we calculated the rake values (Aki and Richards format) and classified the FSP in kinematic classes corresponding to pitch ranges of 0-30° for strike-slip faults, 30-60° for oblique faults, and 60-90° for dip-slip faults (see the Data Record section). 8) We calculated the principal deformation axes from the FSP data and/or from the plane attitude and rake (see the section "Calculation of Deformation axes"), using a combination of MATLAB algorithms 48 for fault-slip kinematic analysis developed for this paper.
Fault/striation pairs and structural sites. The FSPs in the QUIN database refer to meso-and major-scale fault planes (see numbered list for details) surveyed in Structural Sites (SS) located along or near to the Host Fault traces. We did not report fault planes without lineation data as they are unsuitable for kinematic analysis. The SS are separated into four groups, based on their structural features and the position with respect to the Host Faults: 1. SS located along the Host Faults, just on the main fault plane or near it, within the related damage zone (<500 m). In the former (on-fault SS), the FSP data represent both the major fault plane and the associated mesoscopic splays; in the latter (near-fault SS), the FSPs represent the mesoscopic fault planes detected in proximity to the major tectonic contact. The on-fault and near-fault structures are primarily collected in the sectors of the Apennines where normal faults displace, at the surface, carbonate sedimentary successions. These faults are often characterized by spectacular and continuous exposures of fault planes and by highly developed damage zones. For these reasons, they are the most common and frequently detected structures and, therefore, the most numerically present in our database (88.2%) (Fig. 2). The near-fault SS are also observed in sectors where well-stratified, calcareous or siliciclastic turbidite succession crop out 49 . 2. SS of syn-kinematic synthetic and antithetic mesoscopic faults. These are surveyed outside the Host Fault damage zone, most commonly within the hanging wall blocks, at a distance from the major fault trace generally >500 m. These types of SS appear to be particularly widespread within the continental deposits filling the Quaternary syn-tectonic basins. These are ~6.5% of the total. 3. SS of syn-kinematic major and/or mesoscopic faults surveyed along the trace of antithetic structures to the Host Fault. These are ~2.9% of the total. 4. SS of scattered Quaternary mesoscopic fault planes with strike transversal to the major fault alignment (~2.4%).
We report the above classification in our database together with the other information described in the manuscript.

Combination of MATLAB scripts for fault-slip kinematic analysis.
To perform kinematic analysis of fault-slip data, we prepared a new compilation of simple graphical and numerical algorithms in MATLAB 48 valid for: • Calculation of rake from fault and slip vector attitude and sense of motion.
• Calculation of slip vector (trend and plunge) from fault attitude and rake.
• Conversion of rake into pitch.
• Calculation of the conjugate dihedral plane with its slip vector.
• Calculation of deformation axes, assuming variable rupture angles θ between the slip vector and the least extensional axes (P 45 or P 30 in Fig. 3a,b). www.nature.com/scientificdata www.nature.com/scientificdata/ Equivalent calculations and graphical representations are incorporated in other well-known software, such as Faultkin 50,51 , TectonicsFP 1.6.5 (https://github.com/freiter/TectonicsFP.git) (e.g. 52 ,), but, with our in-sequence combination of algorithms, it is possible to obtain all the geometrical-kinematic information (described below) on the FSP in just one export. This makes our code a valuable and easy-to-use tool for fault analysis and representation, usable for seismotectonic and structural geology purposes. A complete guide to using our code is available in the ZENODO repository 48 . www.nature.com/scientificdata www.nature.com/scientificdata/  16 ). (c) Strain ellipse configuration; for an ideal Andersonian condition, the principal strain axes (S1, S2 and S3, where S1 ≥ S2 ≥ S3) are coaxial to the principal stress axes (σ1, σ2 and σ3, where σ1 ≥ σ2 ≥ σ3). The long axis of the finite strain ellipse is the direction of maximum finite stretch (S1); the short axis is the direction of minimum finite stretch (S3); vice versa for the stress ellipsoid. (d) Examples of FSP data stereographic projection (equal-area net, lower hemisphere) using the graphical representation adapted in Andrenacci et al. 48  www.nature.com/scientificdata www.nature.com/scientificdata/ Calculation of deformation axes. The deformation axes, generally referred to as P (contraction), B (neutral) and T (extension), as well as the stress axes, referred to as σ 1 (compression), σ 2 (intermediate) and σ 3 (tension), are the direct representation of fault attitude and sense of slip 15,53 . Both P and T and σ 1 and σ 3 lie on the movement plane 54 , perpendicular to the intermediate or neutral axis, the slip direction being parallel to the maximum resolved shear stress 55 . If the state of stress associated with active faults near the surface is compatible with Anderson's theory, we expect a principal direction to be near-vertical with the other two being near horizontal and perpendicular to each other. Also, an approximation of B, T and P-axes of focal mechanisms with stress-axes may be justified if an angular error of ~15° is accepted between P and σ 1 56 (Fig. 3). There may be significant differences between the principal stress and strain axes in areas with pre-existing fractures. The greatest principal stress (σ 1 ) may occur virtually anywhere within the P-quadrant, and the least principal stress (σ 3 ) likewise anywhere within the T-quadrant 57 . Therefore, the association of a stress field to a given complex fault population needs formal inversion of fault-slip data. Some authors (e.g. 58 ) observe that relevant strain variations occur with proximity to fault tips and that, therefore, only slip-directions from the central portion of the fault are meaningful to constraint regionally significant stress patterns.
Our intent with the QUIN database is to compute, with a simple geometric approach, the likely principal deformation axes of any FSP, given that any striated fault, even if mesoscopic in size, may help to place local geometrical constraints on them 59 .
To compute the three principal deformation axes of each FSP datum, we follow the kinematic method based on the Mohr-Coulomb fracture criterion, known as PBT-Method 16,60 . Data inputs are the attitude of the fault plane and its striation with sense of slip, plus an a priori defined fracture angle θ between the shortening axis and the slip vector on the fault plane. Generally, a constant value of the angle θ for all faults of a given fault system is assumed without considering the anisotropy of the involved materials 16 .
The angle θ between the fault plane and the compressional axis may vary from 0 to 90°. However, in the literature, it is generally assumed to be equal to 45° when considering the dihedral configuration between two complementary planes 53 , as is typical for focal mechanisms, or as 30° when considering the Mohr-Coulomb criterion and the Anderson model 15,61 .
Sippel et al. 16 , among others 61,62 , highlight that an angle of 30° is appropriate for natural fault-slip data at upper crustal levels, as well as for brittle deformation in the laboratory [63][64][65] . A value of 30° is assumed in the World Stress Map for paleostress reconstruction from fault/slip data measuring the P-axis at 30° to fault in plane of slip vector 66 . QUIN 1.0 gives an estimation of deformation axes directions calculated for each FSP, assuming both θ = 30° and = 45°, as two alternative possible kinematic scenarios. The axes calculated with θ = 45° are referred to as P 45 (contraction or shortening), B 45 (neutral) and T 45 (extension or stretching); those calculated with θ = 30° are referred to as P 30 , B 30, and T 30 ( Fig. 3a and b). In both cases, the fault plane contains the intermediate axis (B) and the fault striation with its slip direction and is perpendicular to the movement plane (Fig. 3a). Therefore, an approximation of the P-B-T axes with the principal stress axes (σ 1 ≥ σ 2 ≥ σ 3 ) may be assumed in Andersonian conditions typical at upper crustal depths 15 .
To compute the attitude of the two types of deformation axes, we adopted a simple geometric procedure described in Andrenacci et al. 48 (Fig. 3). We first calculated the attitude of the neutral axis (B) located on the fault plane at an angle of 90° from the slip vector. Then, on the Movement plane, we measured an angle of 30° and 45° toward the vertical to obtain P 30 and P 45 , respectively. Finally, at 90° from P, on the movement plane, we measured T 30  Below we describe the individual records belonging to the three groups.  Table 1.

FSP identification and SS location.
FSP geometry, quality ranking and references. 13) Strike (short name: Strike -expressed in degrees): azimuth angle of a FSP plane with respect to the North. 14) Dip direction (short name: Dip_dir -expressed in degrees): direction of the FSP plane dip with respect to the North, expressed with the right-hand rule strike direction (Table 2) 103 . Unpublished data from this paper are labelled as "PP" (i.e., present paper). An example of this data group is given in Table 2. axis. An example of this data group is given in Table 3.   www.nature.com/scientificdata www.nature.com/scientificdata/ 4) Fault longitude end point (short name: X_end): longitude of the trace end point in decimal degrees (dd. mmmmm) and WGS84 reference frame. 5) Fault latitude end point (short name: Y_end): latitude of the trace end point in decimal degrees (dd. mmmmm) and WGS84 reference frame. 6) Region (short name: Reg): Italian administrative region within the boundaries of which the data is located (In cases where a fault crosses multiple regions, these have been reported from north to south). 7) Host Fault Name (short name: H_F): name of the fault hosting the QUIN 1.0 Structural Sites or neighboring to them. 8) Host Fault Key (HF_key): gives information on the generic eastward or westward dip-direction; the additional term "buried" is used to identify not outcropping faults. 9) Fault System Name (short name: F_S): name of the fault system consisting of a number of along-strike or perpendicular to strike interconnected Host Faults. 10) Fault System Onset (F_S_Onset): the age of the oldest recorded displacement and/or of the oldest syn-tectonic deposits among the Host Faults attributed to the FS. 11) Fault System Seismogenic Activity (F_S_Seism): evidence (yes, no, undetermined) of seismogenic or potentially seismogenic activity from integrated geological and seismological data.

Host
The Host Fault traces are shown in Fig. 1a.

Data Statistical Properties
We show here the statistical properties of the QUIN 1.0 data (Fig. 4). The 3339 FSP data are for ~60% derived from the literature and for ~40% from new observations, all ranked with quality parameters (A, B, C; A is best). When considering the Location Quality Ranking, 37.8% of the FSP data fall in class A, 48.5% in class B and 13.7% in class C. When considering the Data resolution quality ranking, 50.4% of the data fall in class A, 45.6% in class B and 4% in class C (Fig. 4a). The FSP number within each SS varies from a minimum of 1 to a maximum of 46 data. ~50% of the SS have more than 6 FSP. SS with only one or very few FSP data, generally referred to as the major Host Fault plane, although not suitable for forthcoming stress inversion analysis, gives precious kinematic information on less studied or surveyed fault segments.
In Fig. 4b, we subdivided the overall dataset in SS located on west-and east-dipping Host Faults (76% and 24%, respectively) and represented the fault plane attitudes as density contour of the pole distributions. The corresponding best-fit planes dip 56° toward N222° and 52° toward N40, respectively. The FSP data associated with the east-dipping Host Faults (25%) show several mesoscopic antithetic faults (Fig. 4b), whereas the antithetic structures are minimal in association with SS sites located on the west-dipping Host Faults (75%). This difference may be attributed to the different outcropping conditions of the west-and the east-dipping faults. The former tend to occur associated with carbonate rocks and are characterized by a well-defined and easily recognizable main fault plane (Fig. 2). The latter may have a less discrete surface expression, especially where they occur associated with flysch deposits.
In Fig. 4c, the FSP fault kinematics is represented as a histogram (5° bin) of rake angle values. P10, P50 and P90 correspond to rake values of −112°, −88°, −66°, respectively, all falling within the normal fault type kinematics (pitch <60°). The prevailing dip-slip kinematics shown in the rake distribution is not surprising given the uniformity of the intra-Apennine Quaternary tectonic setting 18 and is indicative of the scale invariance of the faulting process outlined by Allmendinger et al. 53 . A small percentage of data (<10%) shows strike-slip kinematics (pitch <30°), but the corresponding tensional axes remain coaxial with extensional deformation in an average SW-NE direction.
The rose diagrams and histograms in Fig. 4d,e represent the attitudes (trend and plunge) calculated for the FSP tensional axes referred to as T (θ = 45°) and T30 (θ = 30°), allowing a preliminary comparison between them.
Whereas T 45 and T 30 are almost coaxial in strike (common mode in direction N45), they significantly differ in plunge (Fig. 4e,g). Both T 45 and T 30 plunge distribution are unimodal but with a substantial difference. T-axes plunge shows the mode at an angle of 20°, with 50% of the data having a dip >20°. T 30 has the mode at an angle of 10°, with 85% of the data having a dip <20°. It appears evident that when assuming the Andersonian conditions, which are reasonable near the surface 15 , the principal deformation axes T 30 -B 30 -P 30 , calculated assuming θ = 30°, assume a near-optimal orientation for most of the FSPs. The least principal strain directions (P) are largely near-vertical and the other two (B and T) near-horizontal. About 75% of the FSP dataset shows a T 30 plunge lower than 20°, versus a value of 50% for T 45 -axes ( Fig. 4d-g).

technical Validation
As mentioned, the QUIN's database represents a collection of published and unpublished data on FSP extracted from tectonic maps, stereographic projections and tabulated data available since the early 1990s. With the lack of tabulated coordinates (i.e., Lat and Long) and fault/slip parameters, the precision in both the SS location and the FSP attitude depends on the degree of resolution of the original information (maps and stereographic projection). For these reasons, the precision is difficult to validate by any designed experiment. Nevertheless, we validated QUIN's data considering two different quality rankings based on the resolution of the source information in terms of the precision of the SS location (Q_loc) and the reproducibility of the fault/slip data (Q_res; see Fig. 4a and Data Record section).
Nearly 60% of the FSP were surveyed by at least one of the authors of this paper (Present Paper and Literature A in Fig. 4a). This implies a general guarantee of homogeneity in FSP survey methodological criteria.
www.nature.com/scientificdata www.nature.com/scientificdata/ www.nature.com/scientificdata www.nature.com/scientificdata/ In databases like the one presented, there are sources of both aleatory and epistemic uncertainty, considered respectively as irreducible, inherent, and due to chance, and reducible, subjective, and due to lack of knowledge 104 . Being able to establish and quantify these uncertainties is a challenge as the data sources are manifold. The first source of aleatoric uncertainties arises from fieldwork, and it regards the precision in measuring fault planes and slickenlines. For newly and recently acquired data (using tablet computers), we performed systematic checks on attitudes using Brunton compasses and the GPS position. Other sources of uncertainties derive from the stages of data acquisition from maps and stereoplots of the literature, which could be a source of operator biases 105,106 . Furthermore, in the case of data reading from stereoplots, the striation may not lie precisely on the fault plane, thus making a correction needed. This type of correction has resulted in being always less than 2° in our database (7 of 3339 > 2°).
We highlight that the FSP rake shows a gaussian peak at −90°, with 606 data (about 18% of overall in the database) showing pure dip-slip kinematics (Fig. 4c). This peak is mainly due to data indicated as "dip-slip" in some of the geologists' old booklets, meant as near pure normal faults. We evaluate that this may imply a rake error in the order of ±5°.
FSP data with strike-slip kinematics are present in a reduced percentage and are randomly distributed. The near sub-horizontal extensional-axis conditions (plunge ≤20°) are achieved by nearly 88% of the T 30 -axes corresponding to FSP with fault plane dip-angle ≥40°, and by nearly 63% of the T 45 -axes corresponding to FSP with fault plane dip-angle ≥25°. In general, the lower plunge values between T 45 -and T 30 -axes are observed for the T 30 -axes for fault dip-angle values ≥53° (~72% of FSP), and for T 45 -axes for fault dip-angle values <53° (~28% of FSP).
We recall that a common selection criterion for data to be inverted or represented as a projection on the horizontal plane is just having a plunge ≤20°, independently from the dynamic or kinematic meaning of the P-and T-axes.
No changes are observed for the neutral axis, which contains the fault direction in both cases. Validation of the QUIN Quaternary database as representative of the Present deformation field can arise from comparing the QUIN's deformation data with the P-B-T ones derived from the upper-crust focal mechanisms of the IPSI database 2 . The co-axiality between the long-term (e.g., Quaternary in this case) and the present-day instantaneous (seismological) deformation field is evident in the stereographic projections of Fig. 4h,i and is even more evident when considering the Andersonian-type strain axes (T 30 -B 30 -P 30 ).

Usage Notes
Possible uses of the QUIN database and supporting Host Fault database are to: 1. verify whether the present configuration of the intra-Apennine Quaternary fault system is developed in the course of a unique regional extensional phase or, instead, it is due to the alternation of non-coaxial extensional phases or extensional and strike-slip phases; 2. verify whether the long-term intra-Apennine Quaternary deformation field is coaxial or not, at the regional and local scales, with the present state of stress derived from focal mechanisms and geodetic data. In case of co-axiality, preliminarily observed comparing the stereographic projections in Fig. 4h,i, the QUIN database will be fundamental to filling spatial information gaps on the crustal state of stress left from instrumental earthquake data; 3. integrate the long-term outcropping deformation pattern derived from QUIN with the present deformation pattern at depth as derived from focal mechanisms to build multi-depth maps of horizontal Stress Trajectories (S H min and max) and tensorial 3-D stress grids; 4. refine and locally extend the surface boundary of the Italian extensional seismogenic province; 5. make available a regional compilation of detailed fault traces and structural data to constrain the geometry and kinematics of the intra-Apennine potentially seismogenic faults, also performing detailed studies on kinematic partitioning and rupture segmentation, both with classical methodologies and with new technologies 11,107-109 ; 6. interpolate the rake angle values among neighboring SS along the Host Fault strike and build gridded rake distributions for fault alignments to be used, for example, as one of the data inputs for fault-based SHA evaluations; 7. represent each SS having a sufficient and kinematically homogeneous fault population as pseudo-focal mechanisms to be compared with seismological focal mechanisms 10,108 ; 8. perform formal fault stress inversion, with different approaches and algorithms, and utilize the regional stress information and the Host Fault attitude to calculate fault-slip tendency 36,110 , fault instability and Coulomb failures scenarios 111 ; 9. once available, the QUIN database can be used for all the other applications identified by the World Stress Map compilers and may bring information on more local stress perturbation which may also be relevant to control fault activation during a multi-source event 10,77,112,113 .
Although generally underused in the active stress database 1,2 , geology-derived fault-slip data may represent a long-term stress regime still operating in an active region, such as Italy. Databases such as QUIN may be helpful for seismotectonic and seismic hazard investigation purposes, especially in areas that have not yet released earthquakes since historical times. In the following months, the database will be extended to southern peninsular Italy, with data recovered from the literature ad newly acquired within the frame of the MUSE-4D seismotectonic project, an Italian national project financed to some of us.

Code availability
The MATLAB code developed for this work is available from ZENODO 48 , together with a complete simple guide that illustrates fundamental steps to perform the kinematic analysis and graphical representation.